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Full-Text Articles in Genetics and Genomics
Evolutionary Interpretations Of Mycobacteriophage Biodiversity And Host-Range Through The Analysis Of Codon Usage Bias, Laura A. Esposito, Swati Gupta, Fraida Streiter, Ashley Prasad, John J. Dennehy
Evolutionary Interpretations Of Mycobacteriophage Biodiversity And Host-Range Through The Analysis Of Codon Usage Bias, Laura A. Esposito, Swati Gupta, Fraida Streiter, Ashley Prasad, John J. Dennehy
Publications and Research
In an genomics course sponsored by the Howard Hughes Medical Institute (HHMI), undergraduate students have isolated and sequenced the genomes of more than 1,150 mycobacteriophages, creating the largest database of sequenced bacteriophages able to infect a single host, Mycobacterium smegmatis, a soil bacterium. Genomic analysis indicates that these mycobacteriophages can be grouped into 26 clusters based on genetic similarity. These clusters span a continuum of genetic diversity, with extensive genomic mosaicism among phages in different clusters. However, little is known regarding the primary hosts of these mycobacteriophages in their natural habitats, nor of their broader host ranges. As such, it …
Machine Learning Meta-Analysis Of Large Metagenomic Datasets: Tools And Biological Insight, Edoardo Pasolli, Duy Tin Truong, Faizan Malik, Levi Waldron, Nicola Segata
Machine Learning Meta-Analysis Of Large Metagenomic Datasets: Tools And Biological Insight, Edoardo Pasolli, Duy Tin Truong, Faizan Malik, Levi Waldron, Nicola Segata
Publications and Research
Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction …
Epigenetic Profiles Signify Cell Fate Plasticity In Unipotent Spermatogonial Stem And Progenitor Cells, Ying Liu, Eugenia G. Giannopoulou, Duacheng Wen, Ilaria Falciatori, Oliver Elemento, C. David Allis, Shahin Rafii, Marco Seandel
Epigenetic Profiles Signify Cell Fate Plasticity In Unipotent Spermatogonial Stem And Progenitor Cells, Ying Liu, Eugenia G. Giannopoulou, Duacheng Wen, Ilaria Falciatori, Oliver Elemento, C. David Allis, Shahin Rafii, Marco Seandel
Publications and Research
Spermatogonial stem and progenitor cells (SSCs) generate adult male gametes. During in vitro expansion, these unipotent murine cells spontaneously convert to multipotent adult spermatogonial-derived stem cells (MASCs). Here we investigate this conversion process through integrative transcriptomic and epigenomic analyses. We find in SSCs that promoters essential to maintenance and differentiation of embryonic stem cells (ESCs) are enriched with histone H3-lysine4 and -lysine 27 trimethylations. These bivalent modifications are maintained at most somatic promoters after conversion, bestowing MASCs an ESC-like promoter chromatin. At enhancers, the core pluripotency circuitry is activated partially in SSCs and completely in MASCs, concomitant with loss of …
Cellmapper: Rapid And Accurate Inference Of Gene Expression In Difficult-To-Isolate Cell Types, Bradlee D. Nelms, Levi Waldron, Luis A. Barrera, Andrew W. Weflen, Jeremy A. Goettel, Guoji Guo, Robert K. Montgomery, Marian R. Neutra, David T. Breault, Scott B. Snapper, Stuart H. Orkin, Martha L. Bulyk, Curtis Huttenhower, Wayne I. Lencer
Cellmapper: Rapid And Accurate Inference Of Gene Expression In Difficult-To-Isolate Cell Types, Bradlee D. Nelms, Levi Waldron, Luis A. Barrera, Andrew W. Weflen, Jeremy A. Goettel, Guoji Guo, Robert K. Montgomery, Marian R. Neutra, David T. Breault, Scott B. Snapper, Stuart H. Orkin, Martha L. Bulyk, Curtis Huttenhower, Wayne I. Lencer
Publications and Research
We present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS.